Abstract

Height measurement for moving pedestrians is quite significant in many scenarios, such as pedestrian positioning, criminal suspect tracking, and virtual reality. Although some existing height measurement methods can detect the height of the static people, it is hard to measure height accurately for moving pedestrians. Considering the height fluctuations in dynamic situation, this paper proposes a real-time height measurement based on the Time-of-Flight (TOF) camera. Depth images in a continuous sequence are addressed to obtain the real-time height of the pedestrian with moving. Firstly, a normalization equation is presented to convert the depth image into the grey image for a lower time cost and better performance. Secondly, a difference-particle swarm optimization (D-PSO) algorithm is proposed to remove the complex background and reduce the noises. Thirdly, a segmentation algorithm based on the maximally stable extremal regions (MSERs) is introduced to extract the pedestrian head region. Then, a novel multilayer iterative average algorithm (MLIA) is developed for obtaining the height of dynamic pedestrians. Finally, Kalman filtering is used to improve the measurement accuracy by combining the current measurement and the height at the last moment. In addition, the VICON system is adopted as the ground truth to verify the proposed method, and the result shows that our method can accurately measure the real-time height of moving pedestrians.

Highlights

  • Whether in reality or in virtual scene, it is crucial to evaluate the height of moving pedestrians

  • We found that the fluctuations of the pedestrian heights all approximately conform to the Gaussian distribution with variance 256, and the variance did not change with the state of the system. erefore, Kalman filtering is further introduced to estimate the pedestrian heights got by (17) to achieve the more accurate real-time heights

  • A real-time height measurement based on the TOF camera is proposed for moving pedestrians

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Summary

Introduction

Whether in reality or in virtual scene, it is crucial to evaluate the height of moving pedestrians. Image processing is devoted to height calculation and correction In this step, a novel multilayer iterative average algorithm based on the actual situation is proposed to remove the outliers and possible noises among the head data. From this figure, we can discover another advantage of the proposed MSER-based segmentation algorithm, which can remove the notable noises in the head region, such as saltand-pepper noise. Note that the red rectangles are the manual markers for easy viewing

Real-Time Calculation for Pedestrian Height
Procedure:
Experiments and Analysis
Methods
Conclusion and Future Work

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